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Yuan Jochen Kang

dblp:185/1666 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1Software engineering, systems software and programming languages · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
2 papers
Program analysis · 77% Debugging and program repair · 18% Software testing · 5%
Network and information security
1 paper
Systems and software security · 100%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis › static analysis
bug detection
0.522016
Automatically Detecting Error Handling Bugs Using Error Specifications · USENIX Security Symposium 2016
APEx: automated inference of error specifications for C APIs · ASE 2016
Debugging and program repair
error-handling bugs
0.212016
Automatically Detecting Error Handling Bugs Using Error Specifications · USENIX Security Symposium 2016
Program analysis › static analysis › bug detection
error handling bug detection
0.212016
APEx: automated inference of error specifications for C APIs · ASE 2016
Program analysis › specification mining
error specification inference
0.212016
APEx: automated inference of error specifications for C APIs · ASE 2016
Software testing › test generation
automated test generation
0.112016
Automatically Detecting Error Handling Bugs Using Error Specifications · USENIX Security Symposium 2016
Program analysis
specification mining
0.112016
Automatically Detecting Error Handling Bugs Using Error Specifications · USENIX Security Symposium 2016

Methods — techniques the papers use, named apart from their topics

static analysis · 0.8usage pattern mining · 0.5
YearPublicationVenuePosition
2016 APEx: automated inference of error specifications for C APIs
abstract
Although correct error handling is crucial to software robustness and security, developers often inadvertently introduce bugs in error handling code. Moreover, such bugs are hard to detect using existing bug-finding tools without correct error specifications. Creating error specifications manually is tedious and error-prone. In this paper, we present a new technique that automatically infers error specifications of API functions based on their usage patterns in C programs. Our key insight is that error-handling code tend to have fewer branching points and program statements than the code implementing regular functionality. Our scheme leverages this property to automatically identify error handling code at API call sites and infer the corresponding error constraints. We then use the error constraints from multiple call sites for robust inference of API error specifications. We evaluated our technique on 217 API functions from 6 different libraries across 28 projects written in C and found that it can identify error-handling paths with an average precision of 94% and recall of 66%. We also found that our technique can infer correct API error specifications with an average precision of 77% and recall of 47%. To further demonstrate the usefulness of the inferred error specifications, we used them to find 118 previously unknown potential bugs (including several security flaws that are currently being fixed by the corresponding developers) in the 28 tested projects.
Yuan Jochen Kang, Baishakhi Ray, Suman Jana
ASE1
2016 Automatically Detecting Error Handling Bugs Using Error Specifications
Suman Jana, Yuan Jochen Kang, Samuel Roth, Baishakhi Ray
USENIX Security Symposium2